Journal of Human Genetics (2011), 1–4& 2011 The Japan Society of Human Genetics All rights reserved 1434-5161/11 $32.00
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ORIGINAL ARTICLE

Computed tomography analysis of the association
between the SH2B1 rs7498665 single-nucleotide
polymorphism and visceral fat area
Kikuko Hotta1, Takuya Kitamoto1, Aya Kitamoto1, Seiho Mizusawa2, Tomoaki Matsuo3, Yoshio Nakata3,
Hideyuki Hyogo4, Hidenori Ochi4, Seika Kamohara5, Nobuyuki Miyatake6, Kazuaki Kotani7, Ryoya Komatsu8,
Naoto Itoh9, Ikuo Mineo10, Jun Wada11, Masato Yoneda12, Atsushi Nakajima12, Tohru Funahashi13,
Shigeru Miyazaki14, Katsuto Tokunaga15, Hiroaki Masuzaki16, Takato Ueno17, Kazuaki Chayama4,
Kazuyuki Hamaguchi18, Kentaro Yamada19, Toshiaki Hanafusa20, Shinichi Oikawa21, Hironobu Yoshimatsu22,
Toshiie Sakata22, Kiyoji Tanaka3, Yuji Matsuzawa7, Kazuwa Nakao1,23 and Akihiro Sekine1,2
Visceral fat accumulation has an important role in increasing morbidity and mortality rate by increasing the risk of developing
several metabolic disorders, such as type 2 diabetes, dyslipidemia and hypertension. New genetic loci that contribute to thedevelopment of obesity have been identified by genome-wide association studies in Caucasian populations. We genotyped 1279
Japanese subjects (556 men and 723 women), who underwent computed tomography (CT) for measuring visceral fat area (VFA)and subcutaneous fat area (SFA), for the following single-nucleotide polymorphisms (SNPs): NEGR1 rs2815752, SEC16B
rs10913469, TMEM18 rs6548238, ETV5 rs7647305, GNPDA2 rs10938397, BDNF rs6265 and rs925946, MTCH2
rs10838738, SH2B1 rs7498665, MAF rs1424233, and KCTD15 rs29941 and rs11084753. In the additive model, none of
the SNPs were significantly associated with body mass index (BMI). The SH2B1 rs7498665 risk allele was found to besignificantly associated with VFA (P¼0.00047) but not with BMI or SFA. When the analysis was performed in men and women
separately, no significant associations with VFA were observed (P¼0.0099 in men and P¼0.022 in women). None of the other
SNPs were significantly associated with SFA. Our results suggest that there is a VFA-specific genetic factor and that apolymorphism in the SH2B1 gene influences the risk of visceral fat accumulation.
Journal of Human Genetics advance online publication, 28 July 2011; doi:10.1038/jhg.2011.86
Keywords: computed tomography; Japanese subjects; obesity; SH2B1; visceral fat area

INTRODUCTION
Obesity, especially visceral fat obesity, is a risk factor for several
metabolic disorders, including type 2 diabetes, dyslipidemia andhypertension.1 Several studies have indicated that adipose tissue,
especially that in the visceral region, secretes various adipocytokines
and that an increase in adipose tissue mass leads to alteration in theplasma levels of adipocytokines, resulting in the development ofdyslipidemia, hypertension, and insulin resistance.2,3 Intra-abdominal
fat accumulation (central adiposity) is determined in terms of waist
circumference; waist-hip ratio; or visceral fat area (VFA), which ismeasured using computed tomography (CT).1,4,5 Recently, two genome-wide association studies were conducted to identify the loci

1EBM Research Center, Kyoto University Graduate School of Medicine, Kyoto, Japan; 2Center for Genomic Medicine, Unit of Genome Informatics, Kyoto University Graduate
School of Medicine, Kyoto, Japan; 3Graduate School of Comprehensive Human Sciences, University of Tsukuba, Tsukuba, Japan; 4Department of Medicine and Molecular
Science, Division of Frontier Medical Science, Programs for Biomedical Research, Graduate School of Biomedical Sciences, Hiroshima University, Hiroshima, Japan; 5Health
Science University, Yamanashi, Japan; 6Department of Hygiene, Faculty of Medicine, Kagawa University, Kagawa, Japan; 7Department of Metabolic Medicine, Graduate School of
Medicine, Osaka University, Osaka, Japan; 8Rinku General Medical Center, Osaka, Japan; 9Toyonaka Municipal Hospital, Osaka, Japan; 10Otemae Hospital, Osaka, Japan;
11Department of Medicine and Clinical Science, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama, Japan; 12Division of
Gastroenterology, Yokohama City University Graduate School of Medicine, Yokohama, Japan; 13Department of Metabolism and Atherosclerosis, Graduate School of Medicine,
Osaka University, Osaka, Japan; 14Tokyo Postal Services Agency Hospital, Tokyo, Japan; 15Itami City Hospital, Hyogo, Japan; 16Division of Endocrinology and Metabolism, Second
Department of Internal Medicine, University of the Ryukyus Faculty of Medicine, Okinawa, Japan; 17Research Center for Innovative Cancer Therapy, Kurume University, Kurume,
Japan; 18Department of Community Health and Gerontological Nursing, Faculty of Medicine, Oita University, Oita, Japan; 19Division of Endocrinology and Metabolism,
Department of Medicine, Kurume University, Kurume, Japan; 20Department of Internal Medicine (I), Osaka Medical College, Osaka, Japan; 21Division of Endocrinology andMetabolism, Department of Medicine, Nippon Medical School, Tokyo, Japan; 22Department of Internal Medicine 1, Faculty of Medicine, Oita University, Oita, Japan and
23Department of Medicine and Clinical Science, Kyoto University Graduate School of Medicine, Kyoto, Japan
Correspondence: Dr K Hotta, Assistant Professor, EBM Research Center, Kyoto University Graduate School of Medicine, Yoshida-Konoecho, Sakyo-ku, Kyoto 606-8501, Japan.
E-mail: kikukoh@kuhp.kyoto-u.ac.jp
Received 6 June 2011; revised 29 June 2011; accepted 30 June 2011

SH2B1 rs7498665 SNP and visceral fat area
K Hotta et al2linked with waist circumference and waist-hip ratio.6,7 In a previous
study, we have reported that the rs1558902 and rs1421085 genotypesof the fat mass and obesity-associated gene (FTO) were significantly
associated with VFA, as well as with subcutaneous fat area (SFA) andbody mass index (BMI).8
We performed a large-scale, case–control association study andfound that secretogranin III (SCG3)9 and myotubularin-related protein 9 (MTMR9)10 conferred susceptibility to an obese phenotype in
the Japanese population. Recent progress in genome-wide association
studies has increased the number of known genetic susceptibility locifor obesity.11–13 Some of the obesity-associated loci identified by the
genome-wide association studies were found to be replicated in theJapanese population.14,15 Some of the obesity-related loci were foundto overlap with the waist circumference waist-hip ratio-related loci, forexample, the loci within the FTO gene and near the melanocortin 4
receptor (MC4R) gene.
In this study, we investigated whether the recently reported obesityrelated loci were associated with VFA, which is an important factor
responsible for increased morbidity and mortality rates.
MATERIALS AND METHODS
Study subjects
In this study, we enrolled 1279 Japanese subjects from outpatient clinics; thesepatients had agreed to undergo CT testing (in the supine position) to
determine the VFA and SFA values at the umbilical level (L4–L5). Both VFA
and SFA values were calculated using the FatScan software program (N2system,
Osaka, Japan).16 The patients visited the hospitals to undergo the treatment forobesity and/or metabolic abnormalities such as hypertension, dyslipidemia andtype 2 diabetes. Patients with secondary obesity and obesity-related hereditarydisorders were excluded from this study. Patients with disease or under
treatment that strongly affect the body weight were also excluded. The clinicaldata were taken at the first visit to the hospital. The clinical characteristics ofthe subjects are summarized in Table 1. Metabolic syndrome and metabolic
abnormalities were diagnosed according to the criteria released by the JapaneseCommittee for the Diagnostic Criteria of Metabolic Syndrome in April 2005.4,5Written informed consent was obtained from each subject, and the protocol
was approved by the ethics committee of each institution and by that of
Kyoto University.

genome-wide association studies in Caucasian populations11–13 and constructed Invader probes (Third Wave Technologies, Madison, WI, USA) for
the following SNPs: rs2815752 in the neuronal growth regulator 1 gene
(NEGR1); rs10913469 in the SEC16 homolog B gene (SEC16B); rs6548238 in
the transmembrane protein 18 gene (TMEM18); rs7647305 in the ets variant 5
gene (ETV5); rs10938397 in the glucosamine-6-phosphate deaminase 2 gene
(GNPDA2); rs6265 and rs925946 in the brain-derived neurotrophic factor gene
(BDNF); rs10838738 in the mitochondrial carrier homolog 2 gene (MTCH2);
rs7498665 in the SH2B adaptor protein 1 gene (SH2B1); rs1424233 in thev-maf musculo-aponeurotic fibrosarcoma oncogene homolog gene (MAF); andrs29941 and rs11084753 in the potassium channel tetramerisation domaincontaining 15 gene (KCTD15). The SNPs were genotyped using Invader assays
as previously described.17 The success rate of these assays was 499.0%.

Statistical analysis
For the additive model, we coded the genotypes as 0, 1 or 2 depending on thenumber of copies of the risk alleles. For the dominant model, homozygosityand heterozygosity with the risk allele were coded as 1 and the other was coded
as 0. Multiple linear regression analyses were carried out to test the independent
effect of the risk alleles on BMI, VFA and SFA by taking into account the effects
of other variables (that is, age and gender) that were assumed to be
independent of the effect of each SNP. The Hardy–Weinberg equilibrium wasassessed using the w2-test.18 Statistical analysis was carried out using thesoftware R (http://www.r-project.org/). P-values were corrected by Bonferroni’s
adjustment and Po0.0042 (0.05/12) was considered statistically significant.

Genomic DNA was extracted from the blood samples collected from eachsubject by using Genomix (Talent Srl, Trieste, Italy). We selected 12 singlenucleotide polymorphisms (SNPs) identified as susceptibility loci for obesity by

RESULTSThe clinical characteristics and genotypes of the subjects are shown in
Tables 1 and 2, respectively. All the SNPs were in the Hardy–Weinberg
equilibrium. The BMI, VFA and SFA values for each SNP genotype
are represented in Table 3. Multiple linear regression analyses of theanthropometric parameters with respect to the 12 SNPs analyzed
are shown in Table 4. No SNPs were not significantly associated withBMI in this population, although a previous study reported that
the SEC16B rs10913469 and TMEM18 rs6548238 SNPs were significantly associated with obesity (BMI430 kg m2) in the Japanese
population.15
The SH2B1 rs7498665 SNP was significantly associated with VFA(P¼0.00047) even when the conservative Bonferroni’s correction wasapplied (Po0.0042). Previous reports indicate that the rs7498665 SNP
is associated with waist circumference19 or visceral fat mass20 in thedominant model. The VFA values of the rs7498665 genotype (Table 3)suggest that the dominant model would be the best-fitted model.
Therefore, we performed multiple regression analyses by using theTable 1 Clinical characteristics of the subjects

Table 2 Genotypic characteristics of the subjects

DNA extraction and single-nucleotide polymorphism genotypingMennAge (years)
BMI (kg m2)
VFA (cm2)
SFA (cm2)
Waist circumference (cm)

Women

556
49.4±12.2
30.2±6.1723
52.2±11.3
28.1±5.31279
51.0±11.8
29.0±5.8

155.3±67.7
206.7±108.6
97.5±11.3

99.8±53.6
241.6±97.2
91.8±10.3

123.9±66.1
226.5±103.7
94.2±11.1

Prevalence of metabolic disease (%)
Dyslipidemia
293 (53)244 (34)537 (42)Hypertension
Impaired fasting glucose

379 (68)
177 (32)452 (63)
176 (24)831 (65)353 (28)

Metabolic syndrome

248 (45)

162 (22)410 (32)

Abbreviations: BMI, body mass index; SFA, subcutaneous fat area; VFA, visceral fat area.
Data are shown as mean±s.d.

Journal of Human Genetics

Allele 1/2

Risk
alleleGenotype

HWE
P-value

NEGR1
SEC16B

A/G
T/C

A
C

1113/163/3
690/510/78

0.24
0.20

rs6548238
rs7647305

TMEM18
ETV5

T/C
T/C

C
C

6/201/1071
201/576/500

0.29
0.10

rs10938397
rs6265

GNPDA2BDNF

A/G
A/G (Met/Val)

G
G

615/537/126
207/609/462

0.58
0.79

rs925946
rs10838738

BDNF
MTCH2

T/G
G/A

T
G

3/100/1175
107/555/616

0.57
0.25

rs7498665

SH2B1

G/A (Ala/Thr)G

29/305/945

0.46

rs1424233
rs29941MAF
KCTD15

A/G
T/C

A
C

726/469/82
774/444/60

0.59
0.72

rs11084753

KCTD15

G/A

G

105/535/638

0.63

Total
SNP ID

Nearby geners2815752
rs10913469

Abbreviations: HWE, Hardy–Weinberg equilibrium; SNP, single-nucleotide polymorphism.

SH2B1 rs7498665 SNP and visceral fat area
K Hotta et al
3

Table 3 Mean BMI, VFA and SFA for 12 obesity-risk variants
Mean±s.d.
BMI (kg m2)
SNP ID

Nearby geners2815752

NEGR1

rs10913469

SEC16B

rs6548238

TMEM18

rs7647305

ETV5

VFA (cm2)

SFA (cm2)

11

12

22

11

12

22

11

12

22

29.1±5.928.8±5.928.3±5.329.2±5.6

28.5±3.1
29.7±6.5

124.8±66.7
123.0±66.4

118.5±62.6
124.9±65.2

226.1±103.1
221.7±103.7

228.3±108.5
231.6±102.6

251.0±79.8
234.0±110.525.9±7.529.0±5.3

29.0±7.2
29.1±5.429.0±5.529.0±6.3

123.4±67.1
124.5±66.3

211.0±135.0
234.1±99.5222.8±111.3
225.6±100.0

227.3±102.2
224.6±109.6

28.8±5.928.6±5.936.0±10.729.1±5.828.7±5.3
29.5±6.1

29.2±5.3
29.6±6.3
28.9±5.785.9±70.6
124.5±66.8
122.7±68.0

95.2±38.8
124.8±70.4
124.3±65.9122.4±68.2
142.6±11.3

124.5±64.0
122.9±64.7123.3±63.3

126.1±67.1
124.0±66.4

224.5±103.4
220.3±92.9
416.8±155.7

227.9±103.3
223.5±102.2

229.3±107.5
233.2±109.9

28.7±4.929.7±4.829.3±6.4
29.5±6.2

28.7±5.3
28.8±5.7

124.5±58.3
134.4±65.3

125.1±68.5
134.5±70.5

122.6±65.2
120.2±64.3

214.1±93.1
231.1±95.9236.3±118.6
233.6±109.6

225.2±101.9
222.2±99.8

29.1±5.729.1±6.0

28.4±3.830.4±6.0

123.1±64.7123.9±65.2

124.0±65.7122.4±67.3

130.6±80.4
136.5±68.5

222.0±102.6
224.8±103.7

235.1±98.4
234.0±109.1
228.2±103.5

223.6±105.5
219.7±74.5
236.6±106.6

29.1±5.828.9±5.8

128.3±71.9

122.5±64.9124.5±66.2

233.0±98.6

227.4±102.0

224.7±106.1

rs10938397

GNPDA2

rs6265BDNF

rs925946

BDNF

rs10838738

MTCH2

rs7498665

SH2B1

rs1424233

MAF

rs29941

KCTD1529.0±6.0
28.8±5.6

rs11084753

KCTD1529.5±5.7

123.2±65.8127.4±66.3

Abbreviations: BMI, body mass index; SFA, subcutaneous fat area; SNP, single-nucleotide polymorphism; VFA, visceral fat area.
11, allele1/allele1; 12, allele1/allele2; 22, allele2/allele2. Allele 1 and allele 2 in each SNP is indicated in Table 2.

Table 4 Relationship between obesity loci and adiposity measures
BMI
SNP ID

Nearby geners2815752
rs10913469

VFA

SFA

b

s.e.

P-valuebs.e.

P-value

NEGR1

0.611

0.448

0.17

7.423

4.847

0.13

6.293

7.978

0.43

SEC16B

0.325

0.255

0.20

2.827

2.753

0.30

4.516

4.532

0.32

b

s.e.

P-value

rs6548238

TMEM18

0.267

0.403

0.51

6.773

4.352

0.12

2.557

7.178

0.72

rs7647305

ETV5

0.025

0.221

0.91

1.984

2.386

0.41

2.565

3.929

0.51

rs10938397

GNPDA2

0.199

0.236

0.40

0.804

2.547

0.75

4.065

4.190

0.33

rs6265

BDNF

0.508

0.223

0.023

1.390

2.410

0.56

6.954

3.968

0.080

rs925946

BDNF

0.816

0.545

0.14

0.390

5.897

0.95

18.972

9.685

0.050

rs10838738

MTCH2

0.162

0.243

0.51

0.292

2.628

0.91

2.726

4.326

0.53

rs7498665

SH2B1

0.536

0.310

0.085

11.7173.343

0.00047

8.341

5.555

0.13

rs1424233

MAF

0.050

0.252

0.84

2.945

2.722

0.28

5.311

4.479

0.24

rs29941

KCTD15

0.481

0.265

0.070

2.588

2.871

0.37

3.589

4.727

0.45

rs11084753

KCTD15

0.332

0.243

0.17

1.562

2.626

0.55

3.242

4.322

0.45

Abbreviations: BMI, body mass index; SFA, subcutaneous fat area; SNP, single-nucleotide polymorphism; VFA, visceral fat area.
Data were derived from a linear regression analysis. BMI, VFA and SFA were adjusted for age and gender.

dominant model and found a significant association between this SNP
and VFA (P¼0.00022). This association remained significant evenafter adjusting for age, gender and BMI in the dominant model(P¼0.00096). The other SNPs did not show any significant association
with VFA. No SNPs, including the SH2B1 rs7498665, were associatedwith SFA.
BMI, VFA and SFA are known to be affected by gender; therefore,
we compared the anthropometric parameters (BMI, VFA and SFA)
among the different genotypes in the men and women (Supplementary Tables 1–3). Association between SH2B1 rs7498665 SNP and VFA
was not significant both in men (P¼0.0099) and women (P¼0.022).
This negative association is most likely due to the decrease in thenumber of each genotype. The VFA values of the rs7498665 genotype(Supplementary Table 2) suggest that the dominant model would be
the best-fitted model both in men and women. By using the dominantmodel, revealed no significant association between the rs7498665
genotype and VFA in men (P¼0.0061) and women (P¼0.015).

To confirm the association of the SH2B1 rs7498665 SNP with VFA,
two SNPs (rs4788102 and rs8049439) in linkage disequilibrium of
rs7498665 reported by previous study11 were genotyped (Supplementary Table 4). Both rs4788102 (P¼0.00058) and rs8049439 (P¼0.0021)
SNPs were significantly associated with VFA.
DISCUSSION
In this study, we showed that the SH2B1 rs7498665 SNP was
significantly associated with VFA. Haupt et al.20 used whole-bodymagnetic resonance imaging to show that this SNP (dominant model)
was associated with visceral fat mass. They also reported that theSH2B1 rs7498665 SNP was not associated with BMI or with nonvisceral fat mass. Jamshidi et al.19 reported that the SH2B1 rs7498665
SNP (dominant model) was associated with waist circumference.
Several studies have reported a negative association between theSH2B1 rs7498665 SNP and abdominal adipose mass (measured
using dual energy X-ray absorptiometry)21 or waist circumference.22,23
Journal of Human Genetics

SH2B1 rs7498665 SNP and visceral fat area
K Hotta et al
4CT- or magnetic resonance imaging-based analyses are more accurate
than waist circumference- and dual energy X-ray absorptiometrybased abdominal fat-mass analysis for evaluating the association
between this SNP and visceral fat mass. These data from this study
and from the study performed by Haupt et al. strongly suggest that theSH2B1 rs7498665 SNP is associated with visceral fat accumulation.
SH2B1 has four splicing isoforms; that is, a, b, g and d, of which
SH2-Bb was originally identified through its association with Janus
kinase 2 (JAK2) protein, a cytoplasmic tyrosine kinase that mediates
cytokine functions.24 SH2B1-knockout mice have been reported toshow severely impaired insulin signaling in the skeletal muscles, liver
and adipose tissue, and progressively develop hyperinsulinemia,
hyperglycemia and glucose intolerance.25 SH2B1-knockout mice also
developed hyperlipidemia, leptin resistance, hyperphagia and obesity.26 Although data for mesenteric fat have not been reported, both
subcutaneous inguinal fat and intra-abdominal (epididymal) fat were
found to be increased in SH2B1-knockout mice.26,27 Neuron-specificrestoration of SH2B1 in knockout mice corrected the metabolic
disorders, improved leptin regulation of orexigenic neuropeptide
expression in the hypothalamus, and protected against high-fat dietinduced leptin resistance and obesity.27 Ventromedial hypothalamic
lesions are reported to induce visceral fat accumulation that does not
result in obesity, and to induce hyperglycemia, hyperinsulinemia andhypertriglyceridemia.28 SH2B1 was specifically expressed in the brain,including the hypothalamus, in mice with neuron-specific SH2B1
restoration.27 Therefore, SH2B1 expression in hypothalamus (possibly
the ventromedial hypothalamic) may have an important role invisceral fat accumulation. As the SH2B1 rs7498665 SNP is a nonsynonymous SNP (G/A, Ala484Thr) and exits in the proline-richregion, the function of the SH2B1 protein might be deteriorated insubjects with the risk G-allele, leading to visceral fat accumulation.
The rs4788102 SNP exists in the 5¢-flanking region of the SH2B1 gene,thus, the expression of SH2B1 may be changed in the subjects with therisk A-allele. It is necessary to investigate whether these SNPs arefunctional.
In summary, we showed that the SH2B1 rs7498665 SNP is significantly associated with VFA. This SNP is not associated with BMI
or SFA, suggesting that there is a VFA-specific genetic factor. Our
results also suggest that the SH2B1 gene has a role in visceral fat
accumulation. However, these results need to be confirmed in otherpopulations.
CONFLICT OF INTEREST
The authors declare no conflict of interest.
ACKNOWLEDGEMENTS
This work was supported by a Grant-in-Aid from the Ministry of Education,
Science, Sports and Culture of Japan (21591186) and by the Mitsui Life Science
Social Welfare Foundation.

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Journal of Human Genetics